Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "80"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 80 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 84 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 82 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 80, Node N11:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459901 not_connected 100.00% 4.65% 100.00% 0.00% - - 10.282229 15.309524 2.065858 4.289053 4.274888 7.146180 10.891100 0.944155 0.2868 0.0432 0.1623 nan nan
2459900 not_connected 100.00% 0.00% 100.00% 0.00% - - 9.138611 15.479982 2.005147 4.687908 4.507950 7.699317 11.905995 0.951353 0.2663 0.0404 0.1723 nan nan
2459898 not_connected 100.00% 0.00% 100.00% 0.00% - - 8.799202 12.676411 2.258104 4.238478 6.410858 9.288524 20.177044 1.693233 0.2989 0.0394 0.2028 nan nan
2459897 not_connected 100.00% 0.00% 100.00% 0.00% - - 8.197016 12.382308 2.588413 4.402796 6.584239 9.975138 18.345717 1.483505 0.3046 0.0377 0.1746 nan nan
2459896 not_connected 100.00% 0.00% 100.00% 0.00% - - 8.452969 12.541067 2.322630 4.491962 8.110873 10.922263 6.192856 0.888236 0.3059 0.0388 0.1752 nan nan
2459895 not_connected 100.00% 0.00% 100.00% 0.00% - - 11.165588 15.349558 3.262942 5.379268 7.385806 10.984688 5.710328 5.499954 0.4331 0.0389 0.2683 nan nan
2459894 not_connected 100.00% 0.00% 100.00% 0.00% - - 9.955230 14.642844 2.426602 3.861354 7.277209 10.500224 15.028655 1.257095 0.3218 0.0401 0.1930 nan nan
2459893 not_connected 100.00% 0.00% 100.00% 0.00% - - 10.195741 15.121292 2.174605 4.252596 6.478583 9.212353 15.157740 2.116395 0.3155 0.0399 0.2018 nan nan
2459892 not_connected 100.00% 0.00% 100.00% 0.00% - - 10.173081 14.934242 2.542551 4.888448 4.752361 7.049599 15.358095 1.389976 0.3088 0.0431 0.2067 nan nan
2459891 not_connected 100.00% 0.00% 100.00% 0.00% - - 9.070364 13.713027 2.924076 4.834553 7.182313 10.327018 20.230524 1.743424 0.2975 0.0390 0.2015 nan nan
2459890 not_connected 100.00% 0.00% 100.00% 0.00% - - 9.427540 13.966013 3.482859 5.511448 6.722455 9.077722 11.727839 0.215937 0.3007 0.0381 0.2027 nan nan
2459889 not_connected 100.00% 0.00% 100.00% 0.00% - - 10.378957 15.774718 2.901145 4.545068 8.613765 12.874528 18.784430 2.032091 0.3088 0.0419 0.2045 nan nan
2459888 not_connected 100.00% 0.00% 100.00% 0.00% - - 8.588176 13.163232 3.127027 5.381604 8.122025 11.764910 5.099406 2.250370 0.3366 0.0403 0.2278 nan nan
2459887 not_connected 100.00% 0.00% 100.00% 0.00% - - 9.307056 14.099841 2.082962 5.291399 5.732992 10.274266 6.820103 1.027353 0.3039 0.0409 0.2037 nan nan
2459886 not_connected 100.00% 0.00% 100.00% 0.00% - - 13.054491 19.098153 2.340247 4.862250 4.922542 8.064162 2.361102 2.056813 0.3923 0.0443 0.2620 nan nan
2459885 not_connected 100.00% 0.00% 100.00% 0.00% - - 16.704168 22.999301 36.994941 25.560499 13.019242 19.302957 18.041112 11.503767 0.3492 0.0394 0.2172 nan nan
2459884 not_connected 100.00% 0.00% 100.00% 0.00% - - 9.103040 13.249204 3.072256 5.140081 6.220163 9.842228 9.624256 0.742396 0.2986 0.0379 0.1984 nan nan
2459883 not_connected 100.00% 0.00% 100.00% 0.00% - - 12.985946 18.372794 32.313557 23.477641 6.817766 10.796847 29.136829 4.431568 0.3089 0.0396 0.2009 nan nan
2459882 not_connected 100.00% 0.00% 100.00% 0.00% - - 22.321905 30.007941 38.287251 25.554463 9.484453 15.186092 16.027490 1.953696 0.3140 0.0410 0.2069 nan nan
2459881 not_connected 100.00% 0.00% 100.00% 0.00% - - 11.950889 17.134457 43.315837 29.341258 17.782567 30.455272 45.693046 14.689472 0.4118 0.0416 0.2530 nan nan
2459880 not_connected 100.00% 0.00% 100.00% 0.00% - - 14.905261 20.794106 34.349076 24.386272 6.024373 9.221975 17.606371 1.548334 0.3011 0.0388 0.2001 nan nan
2459879 not_connected 100.00% 0.53% 100.00% 0.00% - - 8.164821 11.237266 0.526703 4.718519 1.348253 1.955473 16.404800 1.103393 0.2872 0.0380 0.1732 nan nan
2459878 not_connected 100.00% 0.00% 100.00% 0.00% - - 13.343291 18.599109 42.146749 29.522428 10.237715 15.692686 27.725556 4.919671 0.3098 0.0413 0.1755 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 80: 2459901

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
80 N11 not_connected nn Shape 15.309524 10.282229 15.309524 2.065858 4.289053 4.274888 7.146180 10.891100 0.944155

Antenna 80: 2459900

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
80 N11 not_connected nn Shape 15.479982 9.138611 15.479982 2.005147 4.687908 4.507950 7.699317 11.905995 0.951353

Antenna 80: 2459898

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
80 N11 not_connected ee Temporal Discontinuties 20.177044 12.676411 8.799202 4.238478 2.258104 9.288524 6.410858 1.693233 20.177044

Antenna 80: 2459897

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
80 N11 not_connected ee Temporal Discontinuties 18.345717 12.382308 8.197016 4.402796 2.588413 9.975138 6.584239 1.483505 18.345717

Antenna 80: 2459896

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
80 N11 not_connected nn Shape 12.541067 12.541067 8.452969 4.491962 2.322630 10.922263 8.110873 0.888236 6.192856

Antenna 80: 2459895

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
80 N11 not_connected nn Shape 15.349558 11.165588 15.349558 3.262942 5.379268 7.385806 10.984688 5.710328 5.499954

Antenna 80: 2459894

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
80 N11 not_connected ee Temporal Discontinuties 15.028655 14.642844 9.955230 3.861354 2.426602 10.500224 7.277209 1.257095 15.028655

Antenna 80: 2459893

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
80 N11 not_connected ee Temporal Discontinuties 15.157740 10.195741 15.121292 2.174605 4.252596 6.478583 9.212353 15.157740 2.116395

Antenna 80: 2459892

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
80 N11 not_connected ee Temporal Discontinuties 15.358095 14.934242 10.173081 4.888448 2.542551 7.049599 4.752361 1.389976 15.358095

Antenna 80: 2459891

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
80 N11 not_connected ee Temporal Discontinuties 20.230524 9.070364 13.713027 2.924076 4.834553 7.182313 10.327018 20.230524 1.743424

Antenna 80: 2459890

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
80 N11 not_connected nn Shape 13.966013 13.966013 9.427540 5.511448 3.482859 9.077722 6.722455 0.215937 11.727839

Antenna 80: 2459889

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
80 N11 not_connected ee Temporal Discontinuties 18.784430 10.378957 15.774718 2.901145 4.545068 8.613765 12.874528 18.784430 2.032091

Antenna 80: 2459888

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
80 N11 not_connected nn Shape 13.163232 13.163232 8.588176 5.381604 3.127027 11.764910 8.122025 2.250370 5.099406

Antenna 80: 2459887

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
80 N11 not_connected nn Shape 14.099841 14.099841 9.307056 5.291399 2.082962 10.274266 5.732992 1.027353 6.820103

Antenna 80: 2459886

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
80 N11 not_connected nn Shape 19.098153 13.054491 19.098153 2.340247 4.862250 4.922542 8.064162 2.361102 2.056813

Antenna 80: 2459885

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
80 N11 not_connected ee Power 36.994941 22.999301 16.704168 25.560499 36.994941 19.302957 13.019242 11.503767 18.041112

Antenna 80: 2459884

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
80 N11 not_connected nn Shape 13.249204 13.249204 9.103040 5.140081 3.072256 9.842228 6.220163 0.742396 9.624256

Antenna 80: 2459883

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
80 N11 not_connected ee Power 32.313557 18.372794 12.985946 23.477641 32.313557 10.796847 6.817766 4.431568 29.136829

Antenna 80: 2459882

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
80 N11 not_connected ee Power 38.287251 30.007941 22.321905 25.554463 38.287251 15.186092 9.484453 1.953696 16.027490

Antenna 80: 2459881

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
80 N11 not_connected ee Temporal Discontinuties 45.693046 17.134457 11.950889 29.341258 43.315837 30.455272 17.782567 14.689472 45.693046

Antenna 80: 2459880

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
80 N11 not_connected ee Power 34.349076 20.794106 14.905261 24.386272 34.349076 9.221975 6.024373 1.548334 17.606371

Antenna 80: 2459879

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
80 N11 not_connected ee Temporal Discontinuties 16.404800 11.237266 8.164821 4.718519 0.526703 1.955473 1.348253 1.103393 16.404800

Antenna 80: 2459878

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
80 N11 not_connected ee Power 42.146749 18.599109 13.343291 29.522428 42.146749 15.692686 10.237715 4.919671 27.725556
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